The interactions between climate and wildland fire are complex. To better understand these interactions, we used ArcMap 10.2.2 to examine the relationships between early spring snowmelt and total annual area burned within a defined region of the Rocky Mountains of the western United States. Our research methods used Monitoring Trends in Burn Severity (MTBS) fire perimeter data and weekly snow extent provided by the Rutgers Global Snow Lab analysis of National Oceanic and Atmospheric Administration (NOAA) daily snow maps. Our results indicated a significant correlation between early spring snowmelt and total annual area burned (P = 0.0497), providing further evidence that snowmelt timing may be a driving factor for wildland fires. This project builds on the findings of previous studies and provides a novel method for making general predictions about the upcoming fire season months in advance, using freely available remotely sensed data in real time. Further research should apply our model to a broader geographic area, and incorporate higher resolution snowmelt timing data.